In this thesis we study a lightweight framework in which to model knowledge and beliefs and the evolution thereof in multiagent systems. The standard logic used for this is very expressive, but this comes at a high cost in terms of computational efficiency. We here propose a framework which captures more than other existing approaches while remaining cost-effective. In particular, we show its applicability to epistemic planning: given an initial situation and some possible actions, can we find a way to reach our desired goal? This might mean knowing who to ask in order to learn something, making sure we aren't seen when reading someone else's mail, or preventing someone from overhearing our secrets. We also discuss possible extensions to lo...
In reasoning about multi-agent systems, it is important to look beyond the realm of propositional l...
Designing autonomous agents, that interact with others to perform complex tasks, has always been one...
We study the theoretical complexity of reasoning tasks involving knowledge in multi-agent systems. W...
In this thesis we study a lightweight framework in which to model knowledge and beliefs and the evol...
Dans cette thèse nous étudions un cadre simple dans lequel modéliser les croyances et les connaissan...
In this thesis, we propose logical models for belief representation and belief change in a multi-age...
In this thesis, we address the problem of performing event exploration. We define event exploration ...
Single-agent planning in partially observable settings is a well understood problem and existing pla...
Many AI applications involve the interaction of multiple autonomous agents, requiring those agents t...
Classical planning is the problem of finding a sequence of actions that achieve a desired goal from...
Over the last few years, the concept of Artificial Intelligence has become central in different task...
Many AI applications involve the interaction of multiple au-tonomous agents, requiring those agents ...
Single-agent planning in partially observable settings is a well understood problem and existing pla...
International audienceWe introduce a new semantics for a family of logics of explicit and implicit b...
A realistic model of multiagent planning must allow us to model notions which are absent in classica...
In reasoning about multi-agent systems, it is important to look beyond the realm of propositional l...
Designing autonomous agents, that interact with others to perform complex tasks, has always been one...
We study the theoretical complexity of reasoning tasks involving knowledge in multi-agent systems. W...
In this thesis we study a lightweight framework in which to model knowledge and beliefs and the evol...
Dans cette thèse nous étudions un cadre simple dans lequel modéliser les croyances et les connaissan...
In this thesis, we propose logical models for belief representation and belief change in a multi-age...
In this thesis, we address the problem of performing event exploration. We define event exploration ...
Single-agent planning in partially observable settings is a well understood problem and existing pla...
Many AI applications involve the interaction of multiple autonomous agents, requiring those agents t...
Classical planning is the problem of finding a sequence of actions that achieve a desired goal from...
Over the last few years, the concept of Artificial Intelligence has become central in different task...
Many AI applications involve the interaction of multiple au-tonomous agents, requiring those agents ...
Single-agent planning in partially observable settings is a well understood problem and existing pla...
International audienceWe introduce a new semantics for a family of logics of explicit and implicit b...
A realistic model of multiagent planning must allow us to model notions which are absent in classica...
In reasoning about multi-agent systems, it is important to look beyond the realm of propositional l...
Designing autonomous agents, that interact with others to perform complex tasks, has always been one...
We study the theoretical complexity of reasoning tasks involving knowledge in multi-agent systems. W...